feat(config): add searxngURL

src/app/api/models/route.ts

@@ -1,47 +0,0 @@
-import {
-  getAvailableChatModelProviders,
-  getAvailableEmbeddingModelProviders,
-} from '@/lib/providers';
-
-export const GET = async (req: Request) => {
-  try {
-    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
-      getAvailableChatModelProviders(),
-      getAvailableEmbeddingModelProviders(),
-    ]);
-
-    Object.keys(chatModelProviders).forEach((provider) => {
-      Object.keys(chatModelProviders[provider]).forEach((model) => {
-        delete (chatModelProviders[provider][model] as { model?: unknown })
-          .model;
-      });
-    });
-
-    Object.keys(embeddingModelProviders).forEach((provider) => {
-      Object.keys(embeddingModelProviders[provider]).forEach((model) => {
-        delete (embeddingModelProviders[provider][model] as { model?: unknown })
-          .model;
-      });
-    });
-
-    return Response.json(
-      {
-        chatModelProviders,
-        embeddingModelProviders,
-      },
-      {
-        status: 200,
-      },
-    );
-  } catch (err) {
-    console.error('An error occurred while fetching models', err);
-    return Response.json(
-      {
-        message: 'An error has occurred.',
-      },
-      {
-        status: 500,
-      },
-    );
-  }
-};

src/app/api/providers/route.ts

@@ -0,0 +1,28 @@
+import ModelRegistry from '@/lib/models/registry';
+
+export const GET = async (req: Request) => {
+  try {
+    const registry = new ModelRegistry();
+
+    const activeProviders = await registry.getActiveProviders();
+
+    return Response.json(
+      {
+        providers: activeProviders,
+      },
+      {
+        status: 200,
+      },
+    );
+  } catch (err) {
+    console.error('An error occurred while fetching providers', err);
+    return Response.json(
+      {
+        message: 'An error has occurred.',
+      },
+      {
+        status: 500,
+      },
+    );
+  }
+};

src/lib/config.ts

@@ -1,158 +0,0 @@
-import toml from '@iarna/toml';
-
-// Use dynamic imports for Node.js modules to prevent client-side errors
-let fs: any;
-let path: any;
-if (typeof window === 'undefined') {
-  // We're on the server
-  fs = require('fs');
-  path = require('path');
-}
-
-const configFileName = 'config.toml';
-
-interface Config {
-  GENERAL: {
-    SIMILARITY_MEASURE: string;
-    KEEP_ALIVE: string;
-  };
-  MODELS: {
-    OPENAI: {
-      API_KEY: string;
-    };
-    GROQ: {
-      API_KEY: string;
-    };
-    ANTHROPIC: {
-      API_KEY: string;
-    };
-    GEMINI: {
-      API_KEY: string;
-    };
-    OLLAMA: {
-      API_URL: string;
-      API_KEY: string;
-    };
-    DEEPSEEK: {
-      API_KEY: string;
-    };
-    AIMLAPI: {
-      API_KEY: string;
-    };
-    LM_STUDIO: {
-      API_URL: string;
-    };
-    LEMONADE: {
-      API_URL: string;
-      API_KEY: string;
-    };
-    CUSTOM_OPENAI: {
-      API_URL: string;
-      API_KEY: string;
-      MODEL_NAME: string;
-    };
-  };
-  API_ENDPOINTS: {
-    SEARXNG: string;
-  };
-}
-
-type RecursivePartial<T> = {
-  [P in keyof T]?: RecursivePartial<T[P]>;
-};
-
-const loadConfig = () => {
-  // Server-side only
-  if (typeof window === 'undefined') {
-    return toml.parse(
-      fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
-    ) as any as Config;
-  }
-
-  // Client-side fallback - settings will be loaded via API
-  return {} as Config;
-};
-
-export const getSimilarityMeasure = () =>
-  loadConfig().GENERAL.SIMILARITY_MEASURE;
-
-export const getKeepAlive = () => loadConfig().GENERAL.KEEP_ALIVE;
-
-export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
-
-export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
-
-export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
-
-export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
-
-export const getSearxngApiEndpoint = () =>
-  process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
-
-export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
-
-export const getOllamaApiKey = () => loadConfig().MODELS.OLLAMA.API_KEY;
-
-export const getDeepseekApiKey = () => loadConfig().MODELS.DEEPSEEK.API_KEY;
-
-export const getAimlApiKey = () => loadConfig().MODELS.AIMLAPI.API_KEY;
-
-export const getCustomOpenaiApiKey = () =>
-  loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
-
-export const getCustomOpenaiApiUrl = () =>
-  loadConfig().MODELS.CUSTOM_OPENAI.API_URL;
-
-export const getCustomOpenaiModelName = () =>
-  loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
-
-export const getLMStudioApiEndpoint = () =>
-  loadConfig().MODELS.LM_STUDIO.API_URL;
-
-export const getLemonadeApiEndpoint = () =>
-  loadConfig().MODELS.LEMONADE.API_URL;
-
-export const getLemonadeApiKey = () => loadConfig().MODELS.LEMONADE.API_KEY;
-
-const mergeConfigs = (current: any, update: any): any => {
-  if (update === null || update === undefined) {
-    return current;
-  }
-
-  if (typeof current !== 'object' || current === null) {
-    return update;
-  }
-
-  const result = { ...current };
-
-  for (const key in update) {
-    if (Object.prototype.hasOwnProperty.call(update, key)) {
-      const updateValue = update[key];
-
-      if (
-        typeof updateValue === 'object' &&
-        updateValue !== null &&
-        typeof result[key] === 'object' &&
-        result[key] !== null
-      ) {
-        result[key] = mergeConfigs(result[key], updateValue);
-      } else if (updateValue !== undefined) {
-        result[key] = updateValue;
-      }
-    }
-  }
-
-  return result;
-};
-
-export const updateConfig = (config: RecursivePartial<Config>) => {
-  // Server-side only
-  if (typeof window === 'undefined') {
-    const currentConfig = loadConfig();
-    const mergedConfig = mergeConfigs(currentConfig, config);
-    fs.writeFileSync(
-      path.join(path.join(process.cwd(), `${configFileName}`)),
-      toml.stringify(mergedConfig),
-    );
-  }
-};

src/lib/config/serverRegistry.ts

@@ -10,3 +10,5 @@ export const getConfiguredModelProviderById = (
 ): ConfigModelProvider | undefined => {
   return getConfiguredModelProviders().find((p) => p.id === id) ?? undefined;
 };
+
+export const getSearxngURL = () => configManager.getConfig('search.searxngURL', '')

src/lib/config/types.ts

@@ -55,6 +55,9 @@ type Config = {
     [key: string]: any;
   };
   modelProviders: ConfigModelProvider[];
+  search: {
+    [key: string]: any
+  }
 };
 
 type EnvMap = {
@@ -73,6 +76,7 @@ type ModelProviderUISection = {
 type UIConfigSections = {
   general: UIConfigField[];
   modelProviders: ModelProviderUISection[];
+  search:  UIConfigField[];
 };
 
 export type {

src/lib/hooks/useChat.tsx

@@ -20,6 +20,7 @@ import crypto from 'crypto';
 import { useSearchParams } from 'next/navigation';
 import { toast } from 'sonner';
 import { getSuggestions } from '../actions';
+import { MinimalProvider } from '../models/types';
 
 export type Section = {
   userMessage: UserMessage;
@@ -66,13 +67,13 @@ export interface File {
 }
 
 interface ChatModelProvider {
-  name: string;
-  provider: string;
+  key: string;
+  providerId: string;
 }
 
 interface EmbeddingModelProvider {
-  name: string;
-  provider: string;
+  key: string;
+  providerId: string;
 }
 
 const checkConfig = async (
@@ -82,10 +83,12 @@ const checkConfig = async (
   setHasError: (hasError: boolean) => void,
 ) => {
   try {
-    let chatModel = localStorage.getItem('chatModel');
-    let chatModelProvider = localStorage.getItem('chatModelProvider');
-    let embeddingModel = localStorage.getItem('embeddingModel');
-    let embeddingModelProvider = localStorage.getItem('embeddingModelProvider');
+    let chatModelKey = localStorage.getItem('chatModelKey');
+    let chatModelProviderId = localStorage.getItem('chatModelProviderId');
+    let embeddingModelKey = localStorage.getItem('embeddingModelKey');
+    let embeddingModelProviderId = localStorage.getItem(
+      'embeddingModelProviderId',
+    );
 
     const autoImageSearch = localStorage.getItem('autoImageSearch');
     const autoVideoSearch = localStorage.getItem('autoVideoSearch');
@@ -98,145 +101,81 @@ const checkConfig = async (
       localStorage.setItem('autoVideoSearch', 'false');
     }
 
-    const providers = await fetch(`/api/models`, {
+    const res = await fetch(`/api/providers`, {
       headers: {
         'Content-Type': 'application/json',
       },
-    }).then(async (res) => {
-      if (!res.ok)
-        throw new Error(
-          `Failed to fetch models: ${res.status} ${res.statusText}`,
-        );
-      return res.json();
     });
 
-    if (
-      !chatModel ||
-      !chatModelProvider ||
-      !embeddingModel ||
-      !embeddingModelProvider
-    ) {
-      if (!chatModel || !chatModelProvider) {
-        const chatModelProviders = providers.chatModelProviders;
-        const chatModelProvidersKeys = Object.keys(chatModelProviders);
-
-        if (!chatModelProviders || chatModelProvidersKeys.length === 0) {
-          return toast.error('No chat models available');
-        } else {
-          chatModelProvider =
-            chatModelProvidersKeys.find(
-              (provider) =>
-                Object.keys(chatModelProviders[provider]).length > 0,
-            ) || chatModelProvidersKeys[0];
-        }
-
-        if (
-          chatModelProvider === 'custom_openai' &&
-          Object.keys(chatModelProviders[chatModelProvider]).length === 0
-        ) {
-          toast.error(
-            "Looks like you haven't configured any chat model providers. Please configure them from the settings page or the config file.",
-          );
-          return setHasError(true);
-        }
-
-        chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
-      }
-
-      if (!embeddingModel || !embeddingModelProvider) {
-        const embeddingModelProviders = providers.embeddingModelProviders;
-
-        if (
-          !embeddingModelProviders ||
-          Object.keys(embeddingModelProviders).length === 0
-        )
-          return toast.error('No embedding models available');
-
-        embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
-        embeddingModel = Object.keys(
-          embeddingModelProviders[embeddingModelProvider],
-        )[0];
-      }
-
-      localStorage.setItem('chatModel', chatModel!);
-      localStorage.setItem('chatModelProvider', chatModelProvider);
-      localStorage.setItem('embeddingModel', embeddingModel!);
-      localStorage.setItem('embeddingModelProvider', embeddingModelProvider);
-    } else {
-      const chatModelProviders = providers.chatModelProviders;
-      const embeddingModelProviders = providers.embeddingModelProviders;
-
-      if (
-        Object.keys(chatModelProviders).length > 0 &&
-        (!chatModelProviders[chatModelProvider] ||
-          Object.keys(chatModelProviders[chatModelProvider]).length === 0)
-      ) {
-        const chatModelProvidersKeys = Object.keys(chatModelProviders);
-        chatModelProvider =
-          chatModelProvidersKeys.find(
-            (key) => Object.keys(chatModelProviders[key]).length > 0,
-          ) || chatModelProvidersKeys[0];
-
-        localStorage.setItem('chatModelProvider', chatModelProvider);
-      }
-
-      if (
-        chatModelProvider &&
-        !chatModelProviders[chatModelProvider][chatModel]
-      ) {
-        if (
-          chatModelProvider === 'custom_openai' &&
-          Object.keys(chatModelProviders[chatModelProvider]).length === 0
-        ) {
-          toast.error(
-            "Looks like you haven't configured any chat model providers. Please configure them from the settings page or the config file.",
-          );
-          return setHasError(true);
-        }
-
-        chatModel = Object.keys(
-          chatModelProviders[
-            Object.keys(chatModelProviders[chatModelProvider]).length > 0
-              ? chatModelProvider
-              : Object.keys(chatModelProviders)[0]
-          ],
-        )[0];
-
-        localStorage.setItem('chatModel', chatModel);
-      }
-
-      if (
-        Object.keys(embeddingModelProviders).length > 0 &&
-        !embeddingModelProviders[embeddingModelProvider]
-      ) {
-        embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
-        localStorage.setItem('embeddingModelProvider', embeddingModelProvider);
-      }
-
-      if (
-        embeddingModelProvider &&
-        !embeddingModelProviders[embeddingModelProvider][embeddingModel]
-      ) {
-        embeddingModel = Object.keys(
-          embeddingModelProviders[embeddingModelProvider],
-        )[0];
-        localStorage.setItem('embeddingModel', embeddingModel);
-      }
+    if (!res.ok) {
+      throw new Error(
+        `Provider fetching failed with status code ${res.status}`,
+      );
     }
 
+    const data = await res.json();
+    const providers: MinimalProvider[] = data.providers;
+
+    if (providers.length === 0) {
+      throw new Error(
+        'No chat model providers found, please configure them in the settings page.',
+      );
+    }
+
+    const chatModelProvider =
+      providers.find((p) => p.id === chatModelProviderId) ??
+      providers.find((p) => p.chatModels.length > 0);
+
+    if (!chatModelProvider) {
+      throw new Error(
+        'No chat models found, pleae configure them in the settings page.',
+      );
+    }
+
+    chatModelProviderId = chatModelProvider.id;
+
+    const chatModel =
+      chatModelProvider.chatModels.find((m) => m.key === chatModelKey) ??
+      chatModelProvider.chatModels[0];
+    chatModelKey = chatModel.key;
+
+    const embeddingModelProvider =
+      providers.find((p) => p.id === embeddingModelProviderId) ??
+      providers.find((p) => p.embeddingModels.length > 0);
+
+    if (!embeddingModelProvider) {
+      throw new Error(
+        'No embedding models found, pleae configure them in the settings page.',
+      );
+    }
+
+    embeddingModelProviderId = embeddingModelProvider.id;
+
+    const embeddingModel =
+      embeddingModelProvider.embeddingModels.find(
+        (m) => m.key === embeddingModelKey,
+      ) ?? embeddingModelProvider.embeddingModels[0];
+    embeddingModelKey = embeddingModel.key;
+
+    localStorage.setItem('chatModelKey', chatModelKey);
+    localStorage.setItem('chatModelProviderId', chatModelProviderId);
+    localStorage.setItem('embeddingModelKey', embeddingModelKey);
+    localStorage.setItem('embeddingModelProviderId', embeddingModelProviderId);
+
     setChatModelProvider({
-      name: chatModel!,
-      provider: chatModelProvider,
+      key: chatModelKey,
+      providerId: chatModelProviderId,
     });
 
     setEmbeddingModelProvider({
-      name: embeddingModel!,
-      provider: embeddingModelProvider,
+      key: embeddingModelKey,
+      providerId: embeddingModelProviderId,
     });
 
     setIsConfigReady(true);
-  } catch (err) {
+  } catch (err: any) {
     console.error('An error occurred while checking the configuration:', err);
+    toast.error(err.message);
     setIsConfigReady(false);
     setHasError(true);
   }
@@ -356,15 +295,15 @@ export const ChatProvider = ({
 
   const [chatModelProvider, setChatModelProvider] = useState<ChatModelProvider>(
     {
-      name: '',
-      provider: '',
+      key: '',
+      providerId: '',
     },
   );
 
   const [embeddingModelProvider, setEmbeddingModelProvider] =
     useState<EmbeddingModelProvider>({
-      name: '',
-      provider: '',
+      key: '',
+      providerId: '',
     });
 
   const [isConfigReady, setIsConfigReady] = useState(false);
@@ -742,12 +681,12 @@ export const ChatProvider = ({
           ? chatHistory.slice(0, messageIndex === -1 ? undefined : messageIndex)
           : chatHistory,
         chatModel: {
-          name: chatModelProvider.name,
-          provider: chatModelProvider.provider,
+          key: chatModelProvider.key,
+          providerId: chatModelProvider.providerId,
         },
         embeddingModel: {
-          name: embeddingModelProvider.name,
-          provider: embeddingModelProvider.provider,
+          key: embeddingModelProvider.key,
+          providerId: embeddingModelProvider.providerId,
         },
         systemInstructions: localStorage.getItem('systemInstructions'),
       }),

src/lib/models/registry.ts

@@ -4,7 +4,7 @@ import BaseModelProvider, {
 } from './providers/baseProvider';
 import { getConfiguredModelProviders } from '../config/serverRegistry';
 import { providers } from './providers';
-import { ModelList } from './types';
+import { MinimalProvider, Model } from './types';
 
 class ModelRegistry {
   activeProviders: (ConfigModelProvider & {
@@ -35,18 +35,23 @@ class ModelRegistry {
     });
   }
 
-  async getActiveModels() {
-    const models: ModelList[] = [];
+  async getActiveProviders() {
+    const providers: MinimalProvider[] = [];
 
     await Promise.all(
       this.activeProviders.map(async (p) => {
         const m = await p.provider.getModelList();
 
-        models.push(m);
+        providers.push({
+          id: p.id,
+          name: p.name,
+          chatModels: m.chat,
+          embeddingModels: m.embedding,
+        });
       }),
     );
 
-    return models;
+    return providers;
   }
 }
 

src/lib/models/types.ts

@@ -13,4 +13,11 @@ type ProviderMetadata = {
   key: string;
 };
 
-export type { Model, ModelList, ProviderMetadata };
+type MinimalProvider = {
+  id: string;
+  name: string;
+  chatModels: Model[];
+  embeddingModels: Model[];
+};
+
+export type { Model, ModelList, ProviderMetadata, MinimalProvider };

src/lib/providers/aimlapi.ts

@@ -1,94 +0,0 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { getAimlApiKey } from '../config';
-import { ChatModel, EmbeddingModel } from '.';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Embeddings } from '@langchain/core/embeddings';
-import axios from 'axios';
-
-export const PROVIDER_INFO = {
-  key: 'aimlapi',
-  displayName: 'AI/ML API',
-};
-
-interface AimlApiModel {
-  id: string;
-  name?: string;
-  type?: string;
-}
-
-const API_URL = 'https://api.aimlapi.com';
-
-export const loadAimlApiChatModels = async () => {
-  const apiKey = getAimlApiKey();
-
-  if (!apiKey) return {};
-
-  try {
-    const response = await axios.get(`${API_URL}/models`, {
-      headers: {
-        'Content-Type': 'application/json',
-        Authorization: `Bearer ${apiKey}`,
-      },
-    });
-
-    const chatModels: Record<string, ChatModel> = {};
-
-    response.data.data.forEach((model: AimlApiModel) => {
-      if (model.type === 'chat-completion') {
-        chatModels[model.id] = {
-          displayName: model.name || model.id,
-          model: new ChatOpenAI({
-            apiKey: apiKey,
-            modelName: model.id,
-            temperature: 0.7,
-            configuration: {
-              baseURL: API_URL,
-            },
-          }) as unknown as BaseChatModel,
-        };
-      }
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading AI/ML API models: ${err}`);
-    return {};
-  }
-};
-
-export const loadAimlApiEmbeddingModels = async () => {
-  const apiKey = getAimlApiKey();
-
-  if (!apiKey) return {};
-
-  try {
-    const response = await axios.get(`${API_URL}/models`, {
-      headers: {
-        'Content-Type': 'application/json',
-        Authorization: `Bearer ${apiKey}`,
-      },
-    });
-
-    const embeddingModels: Record<string, EmbeddingModel> = {};
-
-    response.data.data.forEach((model: AimlApiModel) => {
-      if (model.type === 'embedding') {
-        embeddingModels[model.id] = {
-          displayName: model.name || model.id,
-          model: new OpenAIEmbeddings({
-            apiKey: apiKey,
-            modelName: model.id,
-            configuration: {
-              baseURL: API_URL,
-            },
-          }) as unknown as Embeddings,
-        };
-      }
-    });
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading AI/ML API embeddings models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/anthropic.ts

@@ -1,78 +0,0 @@
-import { ChatAnthropic } from '@langchain/anthropic';
-import { ChatModel } from '.';
-import { getAnthropicApiKey } from '../config';
-
-export const PROVIDER_INFO = {
-  key: 'anthropic',
-  displayName: 'Anthropic',
-};
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-
-const anthropicChatModels: Record<string, string>[] = [
-  {
-    displayName: 'Claude 4.1 Opus',
-    key: 'claude-opus-4-1-20250805',
-  },
-  {
-    displayName: 'Claude 4 Opus',
-    key: 'claude-opus-4-20250514',
-  },
-  {
-    displayName: 'Claude 4 Sonnet',
-    key: 'claude-sonnet-4-20250514',
-  },
-  {
-    displayName: 'Claude 3.7 Sonnet',
-    key: 'claude-3-7-sonnet-20250219',
-  },
-  {
-    displayName: 'Claude 3.5 Haiku',
-    key: 'claude-3-5-haiku-20241022',
-  },
-  {
-    displayName: 'Claude 3.5 Sonnet v2',
-    key: 'claude-3-5-sonnet-20241022',
-  },
-  {
-    displayName: 'Claude 3.5 Sonnet',
-    key: 'claude-3-5-sonnet-20240620',
-  },
-  {
-    displayName: 'Claude 3 Opus',
-    key: 'claude-3-opus-20240229',
-  },
-  {
-    displayName: 'Claude 3 Sonnet',
-    key: 'claude-3-sonnet-20240229',
-  },
-  {
-    displayName: 'Claude 3 Haiku',
-    key: 'claude-3-haiku-20240307',
-  },
-];
-
-export const loadAnthropicChatModels = async () => {
-  const anthropicApiKey = getAnthropicApiKey();
-
-  if (!anthropicApiKey) return {};
-
-  try {
-    const chatModels: Record<string, ChatModel> = {};
-
-    anthropicChatModels.forEach((model) => {
-      chatModels[model.key] = {
-        displayName: model.displayName,
-        model: new ChatAnthropic({
-          apiKey: anthropicApiKey,
-          modelName: model.key,
-          temperature: 0.7,
-        }) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Anthropic models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/deepseek.ts

@@ -1,49 +0,0 @@
-import { ChatOpenAI } from '@langchain/openai';
-import { getDeepseekApiKey } from '../config';
-import { ChatModel } from '.';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-
-export const PROVIDER_INFO = {
-  key: 'deepseek',
-  displayName: 'Deepseek AI',
-};
-
-const deepseekChatModels: Record<string, string>[] = [
-  {
-    displayName: 'Deepseek Chat (Deepseek V3)',
-    key: 'deepseek-chat',
-  },
-  {
-    displayName: 'Deepseek Reasoner (Deepseek R1)',
-    key: 'deepseek-reasoner',
-  },
-];
-
-export const loadDeepseekChatModels = async () => {
-  const deepseekApiKey = getDeepseekApiKey();
-
-  if (!deepseekApiKey) return {};
-
-  try {
-    const chatModels: Record<string, ChatModel> = {};
-
-    deepseekChatModels.forEach((model) => {
-      chatModels[model.key] = {
-        displayName: model.displayName,
-        model: new ChatOpenAI({
-          apiKey: deepseekApiKey,
-          modelName: model.key,
-          temperature: 0.7,
-          configuration: {
-            baseURL: 'https://api.deepseek.com',
-          },
-        }) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Deepseek models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/gemini.ts

@@ -1,114 +0,0 @@
-import {
-  ChatGoogleGenerativeAI,
-  GoogleGenerativeAIEmbeddings,
-} from '@langchain/google-genai';
-import { getGeminiApiKey } from '../config';
-import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'gemini',
-  displayName: 'Google Gemini',
-};
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Embeddings } from '@langchain/core/embeddings';
-
-const geminiChatModels: Record<string, string>[] = [
-  {
-    displayName: 'Gemini 2.5 Flash',
-    key: 'gemini-2.5-flash',
-  },
-  {
-    displayName: 'Gemini 2.5 Flash-Lite',
-    key: 'gemini-2.5-flash-lite',
-  },
-  {
-    displayName: 'Gemini 2.5 Pro',
-    key: 'gemini-2.5-pro',
-  },
-  {
-    displayName: 'Gemini 2.0 Flash',
-    key: 'gemini-2.0-flash',
-  },
-  {
-    displayName: 'Gemini 2.0 Flash-Lite',
-    key: 'gemini-2.0-flash-lite',
-  },
-  {
-    displayName: 'Gemini 2.0 Flash Thinking Experimental',
-    key: 'gemini-2.0-flash-thinking-exp-01-21',
-  },
-  {
-    displayName: 'Gemini 1.5 Flash',
-    key: 'gemini-1.5-flash',
-  },
-  {
-    displayName: 'Gemini 1.5 Flash-8B',
-    key: 'gemini-1.5-flash-8b',
-  },
-  {
-    displayName: 'Gemini 1.5 Pro',
-    key: 'gemini-1.5-pro',
-  },
-];
-
-const geminiEmbeddingModels: Record<string, string>[] = [
-  {
-    displayName: 'Text Embedding 004',
-    key: 'models/text-embedding-004',
-  },
-  {
-    displayName: 'Embedding 001',
-    key: 'models/embedding-001',
-  },
-];
-
-export const loadGeminiChatModels = async () => {
-  const geminiApiKey = getGeminiApiKey();
-
-  if (!geminiApiKey) return {};
-
-  try {
-    const chatModels: Record<string, ChatModel> = {};
-
-    geminiChatModels.forEach((model) => {
-      chatModels[model.key] = {
-        displayName: model.displayName,
-        model: new ChatGoogleGenerativeAI({
-          apiKey: geminiApiKey,
-          model: model.key,
-          temperature: 0.7,
-        }) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Gemini models: ${err}`);
-    return {};
-  }
-};
-
-export const loadGeminiEmbeddingModels = async () => {
-  const geminiApiKey = getGeminiApiKey();
-
-  if (!geminiApiKey) return {};
-
-  try {
-    const embeddingModels: Record<string, EmbeddingModel> = {};
-
-    geminiEmbeddingModels.forEach((model) => {
-      embeddingModels[model.key] = {
-        displayName: model.displayName,
-        model: new GoogleGenerativeAIEmbeddings({
-          apiKey: geminiApiKey,
-          modelName: model.key,
-        }) as unknown as Embeddings,
-      };
-    });
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading Gemini embeddings models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/groq.ts

@@ -1,44 +0,0 @@
-import { ChatGroq } from '@langchain/groq';
-import { getGroqApiKey } from '../config';
-import { ChatModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'groq',
-  displayName: 'Groq',
-};
-
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-
-export const loadGroqChatModels = async () => {
-  const groqApiKey = getGroqApiKey();
-  if (!groqApiKey) return {};
-
-  try {
-    const res = await fetch('https://api.groq.com/openai/v1/models', {
-      method: 'GET',
-      headers: {
-        Authorization: `bearer ${groqApiKey}`,
-        'Content-Type': 'application/json',
-      },
-    });
-
-    const groqChatModels = (await res.json()).data;
-    const chatModels: Record<string, ChatModel> = {};
-
-    groqChatModels.forEach((model: any) => {
-      chatModels[model.id] = {
-        displayName: model.id,
-        model: new ChatGroq({
-          apiKey: groqApiKey,
-          model: model.id,
-          temperature: 0.7,
-        }) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Groq models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/index.ts

@@ -1,170 +0,0 @@
-import { Embeddings } from '@langchain/core/embeddings';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import {
-  loadOpenAIChatModels,
-  loadOpenAIEmbeddingModels,
-  PROVIDER_INFO as OpenAIInfo,
-  PROVIDER_INFO,
-} from './openai';
-import {
-  getCustomOpenaiApiKey,
-  getCustomOpenaiApiUrl,
-  getCustomOpenaiModelName,
-} from '../config';
-import { ChatOpenAI } from '@langchain/openai';
-import {
-  loadOllamaChatModels,
-  loadOllamaEmbeddingModels,
-  PROVIDER_INFO as OllamaInfo,
-} from './ollama';
-import { loadGroqChatModels, PROVIDER_INFO as GroqInfo } from './groq';
-import {
-  loadAnthropicChatModels,
-  PROVIDER_INFO as AnthropicInfo,
-} from './anthropic';
-import {
-  loadGeminiChatModels,
-  loadGeminiEmbeddingModels,
-  PROVIDER_INFO as GeminiInfo,
-} from './gemini';
-import {
-  loadTransformersEmbeddingsModels,
-  PROVIDER_INFO as TransformersInfo,
-} from './transformers';
-import {
-  loadDeepseekChatModels,
-  PROVIDER_INFO as DeepseekInfo,
-} from './deepseek';
-import {
-  loadAimlApiChatModels,
-  loadAimlApiEmbeddingModels,
-  PROVIDER_INFO as AimlApiInfo,
-} from './aimlapi';
-import {
-  loadLMStudioChatModels,
-  loadLMStudioEmbeddingsModels,
-  PROVIDER_INFO as LMStudioInfo,
-} from './lmstudio';
-import {
-  loadLemonadeChatModels,
-  loadLemonadeEmbeddingModels,
-  PROVIDER_INFO as LemonadeInfo,
-} from './lemonade';
-
-export const PROVIDER_METADATA = {
-  openai: OpenAIInfo,
-  ollama: OllamaInfo,
-  groq: GroqInfo,
-  anthropic: AnthropicInfo,
-  gemini: GeminiInfo,
-  transformers: TransformersInfo,
-  deepseek: DeepseekInfo,
-  aimlapi: AimlApiInfo,
-  lmstudio: LMStudioInfo,
-  lemonade: LemonadeInfo,
-  custom_openai: {
-    key: 'custom_openai',
-    displayName: 'Custom OpenAI',
-  },
-};
-
-export interface ChatModel {
-  displayName: string;
-  model: BaseChatModel;
-}
-
-export interface EmbeddingModel {
-  displayName: string;
-  model: Embeddings;
-}
-
-export const chatModelProviders: Record<
-  string,
-  () => Promise<Record<string, ChatModel>>
-> = {
-  openai: loadOpenAIChatModels,
-  ollama: loadOllamaChatModels,
-  groq: loadGroqChatModels,
-  anthropic: loadAnthropicChatModels,
-  gemini: loadGeminiChatModels,
-  deepseek: loadDeepseekChatModels,
-  aimlapi: loadAimlApiChatModels,
-  lmstudio: loadLMStudioChatModels,
-  lemonade: loadLemonadeChatModels,
-};
-
-export const embeddingModelProviders: Record<
-  string,
-  () => Promise<Record<string, EmbeddingModel>>
-> = {
-  openai: loadOpenAIEmbeddingModels,
-  ollama: loadOllamaEmbeddingModels,
-  gemini: loadGeminiEmbeddingModels,
-  transformers: loadTransformersEmbeddingsModels,
-  aimlapi: loadAimlApiEmbeddingModels,
-  lmstudio: loadLMStudioEmbeddingsModels,
-  lemonade: loadLemonadeEmbeddingModels,
-};
-
-export const getAvailableChatModelProviders = async () => {
-  const models: Record<string, Record<string, ChatModel>> = {};
-
-  for (const provider in chatModelProviders) {
-    const providerModels = await chatModelProviders[provider]();
-    if (Object.keys(providerModels).length > 0) {
-      models[provider] = providerModels;
-    }
-  }
-
-  const customOpenAiApiKey = getCustomOpenaiApiKey();
-  const customOpenAiApiUrl = getCustomOpenaiApiUrl();
-  const customOpenAiModelName = getCustomOpenaiModelName();
-
-  models['custom_openai'] = {
-    ...(customOpenAiApiKey && customOpenAiApiUrl && customOpenAiModelName
-      ? {
-          [customOpenAiModelName]: {
-            displayName: customOpenAiModelName,
-            model: new ChatOpenAI({
-              apiKey: customOpenAiApiKey,
-              modelName: customOpenAiModelName,
-              ...(() => {
-                const temperatureRestrictedModels = [
-                  'gpt-5-nano',
-                  'gpt-5',
-                  'gpt-5-mini',
-                  'o1',
-                  'o3',
-                  'o3-mini',
-                  'o4-mini',
-                ];
-                const isTemperatureRestricted =
-                  temperatureRestrictedModels.some((restrictedModel) =>
-                    customOpenAiModelName.includes(restrictedModel),
-                  );
-                return isTemperatureRestricted ? {} : { temperature: 0.7 };
-              })(),
-              configuration: {
-                baseURL: customOpenAiApiUrl,
-              },
-            }) as unknown as BaseChatModel,
-          },
-        }
-      : {}),
-  };
-
-  return models;
-};
-
-export const getAvailableEmbeddingModelProviders = async () => {
-  const models: Record<string, Record<string, EmbeddingModel>> = {};
-
-  for (const provider in embeddingModelProviders) {
-    const providerModels = await embeddingModelProviders[provider]();
-    if (Object.keys(providerModels).length > 0) {
-      models[provider] = providerModels;
-    }
-  }
-
-  return models;
-};

src/lib/providers/lemonade.ts

@@ -1,94 +0,0 @@
-import axios from 'axios';
-import { getLemonadeApiEndpoint, getLemonadeApiKey } from '../config';
-import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'lemonade',
-  displayName: 'Lemonade',
-};
-
-import { ChatOpenAI } from '@langchain/openai';
-import { OpenAIEmbeddings } from '@langchain/openai';
-
-export const loadLemonadeChatModels = async () => {
-  const lemonadeApiEndpoint = getLemonadeApiEndpoint();
-  const lemonadeApiKey = getLemonadeApiKey();
-
-  if (!lemonadeApiEndpoint) return {};
-
-  try {
-    const res = await axios.get(`${lemonadeApiEndpoint}/api/v1/models`, {
-      headers: {
-        'Content-Type': 'application/json',
-        ...(lemonadeApiKey
-          ? { Authorization: `Bearer ${lemonadeApiKey}` }
-          : {}),
-      },
-    });
-
-    const { data: models } = res.data;
-
-    const chatModels: Record<string, ChatModel> = {};
-
-    models.forEach((model: any) => {
-      chatModels[model.id] = {
-        displayName: model.id,
-        model: new ChatOpenAI({
-          apiKey: lemonadeApiKey || 'lemonade-key',
-          modelName: model.id,
-          temperature: 0.7,
-          configuration: {
-            baseURL: `${lemonadeApiEndpoint}/api/v1`,
-          },
-        }),
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Lemonade models: ${err}`);
-    return {};
-  }
-};
-
-export const loadLemonadeEmbeddingModels = async () => {
-  const lemonadeApiEndpoint = getLemonadeApiEndpoint();
-  const lemonadeApiKey = getLemonadeApiKey();
-
-  if (!lemonadeApiEndpoint) return {};
-
-  try {
-    const res = await axios.get(`${lemonadeApiEndpoint}/api/v1/models`, {
-      headers: {
-        'Content-Type': 'application/json',
-        ...(lemonadeApiKey
-          ? { Authorization: `Bearer ${lemonadeApiKey}` }
-          : {}),
-      },
-    });
-
-    const { data: models } = res.data;
-
-    const embeddingModels: Record<string, EmbeddingModel> = {};
-
-    // Filter models that support embeddings (if Lemonade provides this info)
-    // For now, we'll assume all models can be used for embeddings
-    models.forEach((model: any) => {
-      embeddingModels[model.id] = {
-        displayName: model.id,
-        model: new OpenAIEmbeddings({
-          apiKey: lemonadeApiKey || 'lemonade-key',
-          modelName: model.id,
-          configuration: {
-            baseURL: `${lemonadeApiEndpoint}/api/v1`,
-          },
-        }),
-      };
-    });
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading Lemonade embedding models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/lmstudio.ts

@@ -1,100 +0,0 @@
-import { getKeepAlive, getLMStudioApiEndpoint } from '../config';
-import axios from 'axios';
-import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'lmstudio',
-  displayName: 'LM Studio',
-};
-import { ChatOpenAI } from '@langchain/openai';
-import { OpenAIEmbeddings } from '@langchain/openai';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Embeddings } from '@langchain/core/embeddings';
-
-interface LMStudioModel {
-  id: string;
-  name?: string;
-}
-
-const ensureV1Endpoint = (endpoint: string): string =>
-  endpoint.endsWith('/v1') ? endpoint : `${endpoint}/v1`;
-
-const checkServerAvailability = async (endpoint: string): Promise<boolean> => {
-  try {
-    await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
-      headers: { 'Content-Type': 'application/json' },
-    });
-    return true;
-  } catch {
-    return false;
-  }
-};
-
-export const loadLMStudioChatModels = async () => {
-  const endpoint = getLMStudioApiEndpoint();
-
-  if (!endpoint) return {};
-  if (!(await checkServerAvailability(endpoint))) return {};
-
-  try {
-    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
-      headers: { 'Content-Type': 'application/json' },
-    });
-
-    const chatModels: Record<string, ChatModel> = {};
-
-    response.data.data.forEach((model: LMStudioModel) => {
-      chatModels[model.id] = {
-        displayName: model.name || model.id,
-        model: new ChatOpenAI({
-          apiKey: 'lm-studio',
-          configuration: {
-            baseURL: ensureV1Endpoint(endpoint),
-          },
-          modelName: model.id,
-          temperature: 0.7,
-          streaming: true,
-          maxRetries: 3,
-        }) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading LM Studio models: ${err}`);
-    return {};
-  }
-};
-
-export const loadLMStudioEmbeddingsModels = async () => {
-  const endpoint = getLMStudioApiEndpoint();
-
-  if (!endpoint) return {};
-  if (!(await checkServerAvailability(endpoint))) return {};
-
-  try {
-    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
-      headers: { 'Content-Type': 'application/json' },
-    });
-
-    const embeddingsModels: Record<string, EmbeddingModel> = {};
-
-    response.data.data.forEach((model: LMStudioModel) => {
-      embeddingsModels[model.id] = {
-        displayName: model.name || model.id,
-        model: new OpenAIEmbeddings({
-          apiKey: 'lm-studio',
-          configuration: {
-            baseURL: ensureV1Endpoint(endpoint),
-          },
-          modelName: model.id,
-        }) as unknown as Embeddings,
-      };
-    });
-
-    return embeddingsModels;
-  } catch (err) {
-    console.error(`Error loading LM Studio embeddings model: ${err}`);
-    return {};
-  }
-};

src/lib/providers/ollama.ts

@@ -1,86 +0,0 @@
-import axios from 'axios';
-import { getKeepAlive, getOllamaApiEndpoint, getOllamaApiKey } from '../config';
-import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'ollama',
-  displayName: 'Ollama',
-};
-import { ChatOllama } from '@langchain/ollama';
-import { OllamaEmbeddings } from '@langchain/ollama';
-
-export const loadOllamaChatModels = async () => {
-  const ollamaApiEndpoint = getOllamaApiEndpoint();
-  const ollamaApiKey = getOllamaApiKey();
-
-  if (!ollamaApiEndpoint) return {};
-
-  try {
-    const res = await axios.get(`${ollamaApiEndpoint}/api/tags`, {
-      headers: {
-        'Content-Type': 'application/json',
-      },
-    });
-
-    const { models } = res.data;
-
-    const chatModels: Record<string, ChatModel> = {};
-
-    models.forEach((model: any) => {
-      chatModels[model.model] = {
-        displayName: model.name,
-        model: new ChatOllama({
-          baseUrl: ollamaApiEndpoint,
-          model: model.model,
-          temperature: 0.7,
-          keepAlive: getKeepAlive(),
-          ...(ollamaApiKey
-            ? { headers: { Authorization: `Bearer ${ollamaApiKey}` } }
-            : {}),
-        }),
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading Ollama models: ${err}`);
-    return {};
-  }
-};
-
-export const loadOllamaEmbeddingModels = async () => {
-  const ollamaApiEndpoint = getOllamaApiEndpoint();
-  const ollamaApiKey = getOllamaApiKey();
-
-  if (!ollamaApiEndpoint) return {};
-
-  try {
-    const res = await axios.get(`${ollamaApiEndpoint}/api/tags`, {
-      headers: {
-        'Content-Type': 'application/json',
-      },
-    });
-
-    const { models } = res.data;
-
-    const embeddingModels: Record<string, EmbeddingModel> = {};
-
-    models.forEach((model: any) => {
-      embeddingModels[model.model] = {
-        displayName: model.name,
-        model: new OllamaEmbeddings({
-          baseUrl: ollamaApiEndpoint,
-          model: model.model,
-          ...(ollamaApiKey
-            ? { headers: { Authorization: `Bearer ${ollamaApiKey}` } }
-            : {}),
-        }),
-      };
-    });
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading Ollama embeddings models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/openai.ts

@@ -1,159 +0,0 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { getOpenaiApiKey } from '../config';
-import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'openai',
-  displayName: 'OpenAI',
-};
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Embeddings } from '@langchain/core/embeddings';
-
-const openaiChatModels: Record<string, string>[] = [
-  {
-    displayName: 'GPT-3.5 Turbo',
-    key: 'gpt-3.5-turbo',
-  },
-  {
-    displayName: 'GPT-4',
-    key: 'gpt-4',
-  },
-  {
-    displayName: 'GPT-4 turbo',
-    key: 'gpt-4-turbo',
-  },
-  {
-    displayName: 'GPT-4 omni',
-    key: 'gpt-4o',
-  },
-  {
-    displayName: 'GPT-4o (2024-05-13)',
-    key: 'gpt-4o-2024-05-13',
-  },
-  {
-    displayName: 'GPT-4 omni mini',
-    key: 'gpt-4o-mini',
-  },
-  {
-    displayName: 'GPT 4.1 nano',
-    key: 'gpt-4.1-nano',
-  },
-  {
-    displayName: 'GPT 4.1 mini',
-    key: 'gpt-4.1-mini',
-  },
-  {
-    displayName: 'GPT 4.1',
-    key: 'gpt-4.1',
-  },
-  {
-    displayName: 'GPT 5 nano',
-    key: 'gpt-5-nano',
-  },
-  {
-    displayName: 'GPT 5',
-    key: 'gpt-5',
-  },
-  {
-    displayName: 'GPT 5 Mini',
-    key: 'gpt-5-mini',
-  },
-  {
-    displayName: 'o1',
-    key: 'o1',
-  },
-  {
-    displayName: 'o3',
-    key: 'o3',
-  },
-  {
-    displayName: 'o3 Mini',
-    key: 'o3-mini',
-  },
-  {
-    displayName: 'o4 Mini',
-    key: 'o4-mini',
-  },
-];
-
-const openaiEmbeddingModels: Record<string, string>[] = [
-  {
-    displayName: 'Text Embedding 3 Small',
-    key: 'text-embedding-3-small',
-  },
-  {
-    displayName: 'Text Embedding 3 Large',
-    key: 'text-embedding-3-large',
-  },
-];
-
-export const loadOpenAIChatModels = async () => {
-  const openaiApiKey = getOpenaiApiKey();
-
-  if (!openaiApiKey) return {};
-
-  try {
-    const chatModels: Record<string, ChatModel> = {};
-
-    openaiChatModels.forEach((model) => {
-      // Models that only support temperature = 1
-      const temperatureRestrictedModels = [
-        'gpt-5-nano',
-        'gpt-5',
-        'gpt-5-mini',
-        'o1',
-        'o3',
-        'o3-mini',
-        'o4-mini',
-      ];
-      const isTemperatureRestricted = temperatureRestrictedModels.some(
-        (restrictedModel) => model.key.includes(restrictedModel),
-      );
-
-      const modelConfig: any = {
-        apiKey: openaiApiKey,
-        modelName: model.key,
-      };
-
-      // Only add temperature if the model supports it
-      if (!isTemperatureRestricted) {
-        modelConfig.temperature = 0.7;
-      }
-
-      chatModels[model.key] = {
-        displayName: model.displayName,
-        model: new ChatOpenAI(modelConfig) as unknown as BaseChatModel,
-      };
-    });
-
-    return chatModels;
-  } catch (err) {
-    console.error(`Error loading OpenAI models: ${err}`);
-    return {};
-  }
-};
-
-export const loadOpenAIEmbeddingModels = async () => {
-  const openaiApiKey = getOpenaiApiKey();
-
-  if (!openaiApiKey) return {};
-
-  try {
-    const embeddingModels: Record<string, EmbeddingModel> = {};
-
-    openaiEmbeddingModels.forEach((model) => {
-      embeddingModels[model.key] = {
-        displayName: model.displayName,
-        model: new OpenAIEmbeddings({
-          apiKey: openaiApiKey,
-          modelName: model.key,
-        }) as unknown as Embeddings,
-      };
-    });
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading OpenAI embeddings models: ${err}`);
-    return {};
-  }
-};

src/lib/providers/transformers.ts

@@ -1,36 +0,0 @@
-import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
-
-export const PROVIDER_INFO = {
-  key: 'transformers',
-  displayName: 'Hugging Face',
-};
-
-export const loadTransformersEmbeddingsModels = async () => {
-  try {
-    const embeddingModels = {
-      'xenova-bge-small-en-v1.5': {
-        displayName: 'BGE Small',
-        model: new HuggingFaceTransformersEmbeddings({
-          modelName: 'Xenova/bge-small-en-v1.5',
-        }),
-      },
-      'xenova-gte-small': {
-        displayName: 'GTE Small',
-        model: new HuggingFaceTransformersEmbeddings({
-          modelName: 'Xenova/gte-small',
-        }),
-      },
-      'xenova-bert-base-multilingual-uncased': {
-        displayName: 'Bert Multilingual',
-        model: new HuggingFaceTransformersEmbeddings({
-          modelName: 'Xenova/bert-base-multilingual-uncased',
-        }),
-      },
-    };
-
-    return embeddingModels;
-  } catch (err) {
-    console.error(`Error loading Transformers embeddings model: ${err}`);
-    return {};
-  }
-};

src/lib/searxng.ts

@@ -1,5 +1,5 @@
 import axios from 'axios';
-import { getSearxngApiEndpoint } from './config';
+import { getSearxngURL } from './config/serverRegistry';
 
 interface SearxngSearchOptions {
   categories?: string[];
@@ -23,7 +23,7 @@ export const searchSearxng = async (
   query: string,
   opts?: SearxngSearchOptions,
 ) => {
-  const searxngURL = getSearxngApiEndpoint();
+  const searxngURL = getSearxngURL();
 
   const url = new URL(`${searxngURL}/search?format=json`);
   url.searchParams.append('q', query);